Patients' Experiences and Perceptions of the Symptom Screening with Targeted Early Palliative Care (STEP) Process
Bibliographic record
Abstract
Symptom screening with Targeted Early Palliative care (STEP) is a novel intervention offering early palliative care to symptomatic patients with advanced cancer. A qualitative descriptive approach was taken to explore patients’ experiences and perceptions of the STEP process and to identify factors considered when deciding to accept or decline a palliative care clinic (PCC) referral. Fifteen patients completed interviews. Participants stated they believed symptom screening helped healthcare providers, but emphasized the additional importance of discussing their symptom scores. Some participants felt shocked/discouraged, and others comforted/supported at being offered a PCC referral; benefits of receiving a referral were noted. Common factors considered when deciding to accept or decline a referral were: perceived symptom burden, perceived need for additional support, and readiness to contemplate a terminal prognosis. This information is important to guide future implementations of STEP and to ensure that timely palliative care is provided to those in greatest need.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".